Multimodal ML Engineer

Full Time Senior

Job description

We're looking for a Multimodal ML Engineer to join White Circle, an AI Safety company building the policy enforcement and optimization layer for AI systems. Backed by $11M from senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, and DeepMind, White Circle processes 100M+ API calls monthly and runs its own LLMs in production.

You will

Train and fine-tune large-scale multimodal models (vision-language, audio, speech, video) from scratch and from pretrained checkpoints.
Design experiments, build multimodal data pipelines, and train MoE architectures.
Build alignment pipelines (SFT, DPO, GRPO), optimize for production (quantization, distillation, streaming), and deploy end-to-end.
Define evaluation metrics that actually matter for the product.

Requirements

3+ years training large-scale multimodal models.
Strong PyTorch and distributed training experience (DeepSpeed, FSDP).
Deep familiarity with multimodal architectures – LLaVA, Qwen-VL, InternVL, Audio Flamingo, Whisper, HuBERT, Conformer or similar.
Hands-on RLHF/alignment across modalities (GRPO, DPO, reward modeling).
Both audio and video experience required – sequence modeling for each, plus large-scale dataset curation and production inference optimization.
Relocation to Paris or London (hybrid) required.

Bonus

Audio signal processing fundamentals – spectrograms, mel features, noise reduction.
MoE architecture experience.

We offer

$100k–$250k/year salary + equity; higher figures can be negotiated.
Official employment, visa and relocation help.

Compensation: $100K – $250K • Higher figures and equity are negotiable

• $100K – $250K • Higher figures and equity are negotiable

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Required skills

production pytorch paris equity visa hybrid experiments openai london llms relocation distillation dpo video whisper audio signal processing anthropic streaming alignment audio huggingface speech mistral evaluation metrics multimodal models distributed training policy enforcement ai systems noise reduction reward modeling ai safety deepmind quantization deepspeed rlhf inference optimization sft fsdp api calls optimization layer grpo dataset curation multimodal ml engineer pretrained checkpoints moe architectures alignment pipelines llava qwen-vl internvl audio flamingo hubert conformer sequence modeling spectrograms mel features vision-language multimodal data pipelines end-to-end deployment multimodal architectures audio experience video experience

Multimodal ML Engineer

Job description

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